Sharif Digital Repository

The advent of various real-time multimedia applications in high-speed networks creates a need for quality of service (QoS) based multicast routing. Two important QoS constraints are the bandwidth constraint and the end-to-end delay constraint. The QoS based multicast routing problem is a known NP-complete problem that depends on (1) bounded end-to-end delay and link bandwidth along the paths from the source to each destination, and (2) minimum cost of the multicast tree. In this paper we describe a new representation, called node parent index (NPI) representation, for representing trees and describe harmony operations accord to this representation. The presented algorithm is based on the... 

In this paper, the extended finite element method is presented for thermo-hydro-mechanical (THM) modeling of impermeable discontinuities in saturated porous media. The X-FEM technique is applied to the THM governing equations for the spatial discretization, followed by a generalized Newmark scheme for the time domain discretization. The displacement field is enriched by the Heaviside and crack tip asymptotic functions, and the pressure and temperature fields are enriched by the Heaviside and appropriate asymptotic functions. The process is accomplished by partitioning the domain with triangular sub-elements. Numerical examples are presented to demonstrate the capability of proposed technique... 

With the development of computing systems for data processing, the image processing and image analyzing methods have been developed on the basis of pixel assessment. These methods can analyze and detect the images by assigning a value for each pixel and using the matrices calculations. In the present research, two methods have been used to assess the simulated material microstructures. In the first method, the vertices of the microstructure are counted to determine accurately the mean grain size by the Euler's relationship, while in the second method, the image processing and image analyzing methods are utilized to assess the microstructure image. To verify the accuracies of the methods... 

The advent of various real-time multimedia applications in high-speed networks creates a need for quality of service (QoS) based multicast routing. Two important QoS constraints are the bandwidth constraint and the end-to-end delay constraint. The QoS based multicast routing problem is a known NP-complete problem that depends on (1) bounded end-to-end delay and link bandwidth along the paths from the source to each destination, and (2) minimum cost of the multicast tree. In this paper, we presents novel centralized algorithms to solve the bandwidth-delay-constrained least-cost multicast routing problem based on the harmony search (HS) algorithm. Our first algorithm uses modified Prüfer... 

The prediction of material microstructure is of great interest to the material designers since the property and performance of materials depend strongly on their microstructures. In this work, a Monte Carlo approach is used to investigate the normal grain growth of aluminum and pure copper. The grain growth was calculated at certain temperatures using the grain growth law and compared with the simulation results by varying the Q as a parameter of simulation lattice orientation for pure aluminum. Also the results predicted by the Monte Carlo method showed a good agreement with the experimental results of grain growth of pure cooper. It was found that increase in Q increases the accuracy of... 

The prediction of material microstructure is of great interest to the material designers since the property and performance of materials depend strongly on their microstructures. In this research the Monte Carlo method and grain growth phenomenon have been used to predict the limiting grain size in the presence of second phase particles. The results showed a good agreement with the previous published results predicted by the analytical models. It was found that the lattice orientation parameter, Q, strongly affects the kinetic of the grain growth. The experimental and theoretical results of limiting grain size predicted by Monte Carlo method showed that by decreasing the value of Q the... 

We present an efficient and provably-secure e-voting protocol, which is a variant of the JCJ e-votingprotocol (Juels et al., 2010). It decreases the total number of JCJ's operations from O(n2) to O(n), where n is the number of votes or voters (whichever is the maximum). Note that since the operations under consideration are time-consuming (e.g., public-key encryption), the improvement is quite substantial. As a rough comparison, consider a nation-wide election with around ten million voters/votes. Assuming each operation takes one microsecond, and no parallelization is used, one can see a huge difference: our protocol tallies the votes in 10 seconds, while the JCJ protocol requires over 3... 

Distributed generation (DG) units are increasingly installed in the power systems. Distribution companies (DisCo) can opt to purchase the electricity from DG in an energy purchase contract to supply the customer demand and reduce energy loss. This paper proposes a framework for optimal contract pricing of independent dispatchable DG units considering competition among them. While DG units tend to increase their profit from the energy purchase contract, DisCo minimizes the demand supply cost. Multi-leader follower game theory concept is used to analyze the situation in which competing DG units offer the energy price to DisCo and DisCo determines the DG generation. A bi-level approach is used... 

Chevallier-Mames et al, proved that in a specific condition (such as the lack of untappable channels and trusted-third parties), the universal verifiability and privacy-preserving properties of e-voting protocols are incompatible (WOTE'06 and TTE'10). In this paper, we first show a flaw in their proof. Then, we prove that even with more assumptions, such as the existence of TTPs and untappable channels between the authorities, an e-voting protocol is unable to preserve privacy, regardless of verifiability. Finally, we demonstrate that preserving privacy in e-voting protocols requires the provision of at least one of the following assumptions: limited computational power of adversary,... 

In this paper, the crack growth simulation is presented in saturated porous media using the extended finite element method. The mass balance equation of fluid phase and the momentum balance of bulk and fluid phases are employed to obtain the fully coupled set of equations in the framework of u - p formulation. The fluid flow within the fracture is modeled using the Darcy law, in which the fracture permeability is assumed according to the well-known cubic law. The spatial discritization is performed using the extended finite element method, the time domain discritization is performed based on the generalized Newmark scheme, and the non-linear system of equations is solved using the... 

In this paper with the use of fuzzy genetic algorithm combination with evolutionary algorithms, as a method for local searching, it has been tried to exploit high capabilities of genetic algorithm, as a search algorithm, beside to other evolutionary algorithms, as local search algorithms, in order to increase efficiency of a rule learning system. For this purpose three hybrid algorithms have been used for solving the intrusion detection problem. These three algorithms are combination of genetic algorithm and SFL and PSO as three evolutionary algorithms which try to introduce efficient solutions for complex optimization problems by patterning from natural treatments. © 2007 IEEE  

The shale volume in the formation affects the petrophysical parameters of the reservoir, such as porosity, permeability, and saturation. Since these parameters indicate the amount of hydrocarbon in the reservoir and the reservoir producibility, shale volume determination is an essential challenge in the oil industry. This study compares conventional methods and Machine Learning (ML) algorithms to estimate the shale volume in the Fahliyan Formation in one of the oil fields in southern Iran. In this regard, the shale volume of the formation was calculated using Gamma-Ray (GR), Density-Neutron (DN), and Density-Sonic (DS) as well as ML methods such as Artificial Neural Networks (ANN), Support... 

Physics-informed neural networks (PINNs) have received significant attention as a unified framework for forward, inverse, and surrogate modeling of problems governed by partial differential equations (PDEs). Training PINNs for forward problems, however, pose significant challenges, mainly because of the complex non-convex and multi-objective loss function. In this work, we present a PINN approach to solving the equations of coupled flow and deformation in porous media for both single-phase and multiphase flow. To this end, we construct the solution space using multi-layer neural networks. Due to the dynamics of the problem, we find that incorporating multiple differential relations into the...